Stars
Completely free and open-source human-like Instagram bot. Powered by UIAutomator2 and compatible with basically any Android device 5.0+ that can run Instagram - real or emulated.
Fit interpretable models. Explain blackbox machine learning.
Companion application for Video DownloadHelper browser add-on
MILTON: Disease prediction with biomarkers and augmented PheWAS analyses
Official Implementation of "Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models".
A fast, simple, recursive content discovery tool written in Rust.
ππ€ Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper
completely free for everyone. Its build-in Flutter Dart.
Use ArXiv ChatGuru to talk to research papers. This app uses LangChain, OpenAI, Streamlit, and Redis as a vector database/semantic cache.
π Software Developer Portfolio Template that helps you showcase your work and skills as a software developer. (This is currently not being actively maintained)
React Components for AI Chat π¬ π
M3NetFlow: a novel multi-scale multi-hop multi-omics graph AI model for omics data integration and interpretation
Build the graph model from UCSC and ROSMAP dataset
[The Web Conference 2024] GNNShap: Scalable and Accurate GNN Explanation using Shapley Values
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports compβ¦
A Python web application calling Microsoft graph that is secured using the Microsoft identity platform
This is a repo for migration of CROssBAR data to the Neo4j database via BioCypher
A meta-graph of BioCypher modular adapters, created by a BioCypher pipeline
Template for creating a BioCypher-driven knowledge graph
PheKnowLator: Heterogeneous Biomedical Knowledge Graphs and Benchmarks Constructed Under Alternative Semantic Models
Backend library for conversational AI in biomedicine
A unifying framework for biomedical research knowledge graphs
π§βπ« 60+ Implementations/tutorials of deep learning papers with side-by-side notes π; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gaβ¦